Skip to content

Smart Chains, Fresh Gains

Sep 2026 · 44 references
Food Supply Chain Traceability

Abstract

High post-harvest losses, significant greenhouse gas emissions, and system inefficiencies in conventional refrigeration and monitoring systems all provide major problems for the worldwide cold chain for perishable items. This chapter looks at how Artificial Intelligence (AI), Internet of Things (IoT) sensors, digital twins, blockchain, and edge computing are changing sustainable food delivery by themselves and in combination. It discusses restrictions of conventional cold chains, such isolated data, reactive decision-making, and regional differences in losses, and describes sophisticated technical designs such layered IoT networks, AI-driven anomaly detection, predictive analytics, and self-optimizing digital twins. Real-world uses by companies including Maersk and Walmart together with benefits for SMEs in developing nations prove these advances. It examines the significant challenges like high costs, interoperability issues, cybersecurity threats, and skill shortages and offers solutions using open standards, legislation incentives, phased implementation, and ethical guidelines.

View source

Similar papers

#computer vision Review Sep 2017

Agile Software Development Methods: Review and Analysis

This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.

P. Abrahamsson, O. Salo, Jussi Ronkainen et al. · 727 citations · ⚡54
#computer vision Jun 2008

The impact of agile practices on communication in software development

The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.

M. Pikkarainen, Jukka Haikara, O. Salo et al. · 401 citations · ⚡48
#machine learning Review Open access Oct 2014

Software development in startup companies: A systematic mapping study

The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al. · 394 citations · ⚡54

Related blog posts

Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.